Quantifying the performance differences between PVM and TreadMarks

doi:10.1006/jpdc.1997.1332

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Quantifying the performance differences between PVM and TreadMarks

1997-06-01

DOI：10.1006/jpdc.1997.1332

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Abstract

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This paper compares two systems for parallel programming on networks of workstations: Parallel Virtual Machine (PVM), a message-passing system, and TreadMarks, a software distributed shared-memory (DSM) system, The eight applications used in this comparison are Water and Barnes-Hut from the SPLASH benchmark suite; 3-D FFT, Integer Sort (IS), and Embarrassingly Parallel (EP) from the NAS benchmarks; ILINK, a widely used genetic linkage analysis program; and Successive Over-Relaxation (SOR) and Traveling Salesman (TSP), Two different input data sets are used for five of the applications, We use two execution environments, The first is a 155 Mbps ATM network with eight Spare-20 model 61 workstations; the second is an eight-processor IBM SP/2. The differences in speedup between TreadMarks and PVM depend mostly on the applications, and only to a much lesser extent on the platform and the data set used, In particular, the TreadMarks speedup for six of the eight applications is within 15% of that achieved with PVM, For one application, the difference in speedup is between 15% and 30%, and for another, the difference is around 50%, We identified four important factors that contribute to the lower performance of TreadMarks: (1) extra messages due to the separation of synchronization and data transfer, (2) extra messages to handle access misses caused by the use of an invalidate protocol, (3) false sharing, and (4) diff accumulation for migratory data, We have quantified the effects of the last three factors by measuring the performance gain when each is eliminated, Of the three factors, TreadMarks' use of a separate request message per page of data accessed is the most important. The effect of false sharing is comparatively low Reducing diff accumulation benefits migratory data only when the diffs completely overlap, When these performance impediments are removed, all of the TreadMarks programs perform within 25% of PVM, and for six out of eight experiments, TreadMarks is less than 5% slower than PVM. (C) 1997 Academic Press.

Keywords:

LINKAGE ANALYSIS

MEMORY-SYSTEMS

ARCHITECTURES

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